Abstract:
Selectionism emphasizes carving patterns, memes remind us of minimal replicable
patterns, but a full-fledged Darwinian process needs six essential ingredients
to keep going, to recursively bootstrap quality
from rude beginnings. While there may be situations ("sparse Darwinism") in which a reduced number suffice, another five ingredients, while not essential, greatly enhance the speed and stability of a Darwinian process. While our best examples are drawn from species evolution, the immune response, and evolutionary epistemology, the Darwinian process may well be a major law of the universe, right up there with chemical bonds as
a prime generator of interesting combinations that discover stratified
stabilities.

Since Richard Dawkins' The
Extended Phenotype got me to thinking about copying units in the
mid-1980s, I have been trying to define a cerebral code (the spatiotemporal
firing pattern that represents a word, image, metaphor, or even a sentence)
by searching for what can be successfully replicated in the brain's neural
circuitry, a minimum replicable unit.
I indeed found such circuitry (it implies that the firing pattern within several hundred minicolumns of
neocortex, contained in a 0.5 mm hexagon, is such a copying unit). But to explore creativity in higher intellectual function, I wanted
to see if the resulting copies could compete in a Darwinian manner, the
process shaping up quality as it goes. And that forced me to try and boil
down a lot of evolutionary biology, attempting to abstract the features
that were essential (for what I came to call "the full-fledged Darwinian
process") from those that merely contributed to speed or stability.
This isn't the place to describe the neural outcome -- it's in The Cerebral Code
and, more briefly, in the seventh chapter of my other 1996 book, How
Brains Think -- but this does seem an appropriate place to review
what I started calling "The Six Essentials." They seem applicable
to a wide range of problems within memetics9
as the field attempts to cope with evolutionary models of information transmission. For a more general history of memetics, see the useful bibliographies22 of
McMullin, Speel, and Wilkins; I will only mention a few (mostly cautionary!) contributions from neuroscience along the way.

Selectionism

Looking back into the history of biology, it appears that wherever a
phenomenon resembles learning, an instructive theory was first proposed
to account for the underlying mechanisms. In every case, this was later
replaced by a selective theory. Thus the species were thought to have developed
by learning or by adaptation of individuals to the environment, until Darwin
showed this to have been a selective process. Resistance of bacteria to
antibacterial agents was thought to be acquired by adaptation, until Luria
and Delbrück showed the mechanism to be a selective one. Adaptive
enzymes were shown by Monod and his school to be inducible enzymes arising
through the selection of preexisting genes. Finally, antibody formation
that was thought to be based on instruction by the antigen is now found
to result from the selection of already existing patterns. It thus remains
to be asked if learning by the central nervous system might not also be
a selective process; i.e., perhaps learning is not learning either.

The term "selectionism" covers a wide
range of cases, ranging from fancy biology with sexual selection to examples
that are called "selective survival" because they lack any notion
of replication. Brain development offers many examples of this simple end
of selectionism.

The environment affects survival of cells and their interconnections,
and thus helps to create patterns during development (so-called "epigenetic
factors in development"). For example, the neural development of a
single individual exhibits an enormous overproduction of connections between
neurons. Most such synapses (and even long axon branches) disappear, raising
notions of selective survival (J. Z. Young's 1964
proposal15, that synapses were selectively weakened, was what started this
whole line of reasoning).

Neurons themselves are also overproduced and die. This again might allow
memories to be stored by a carving process (that was Dawkins'
1971 proposal5) but it turns out that most neuron death occurs during gestation.

If the removal of connections or cells is carried too far (a common problem
in carving wood blocks for printing), there may be no way back (unless, of course, unmodified copies survive elsewhere). Selective strengthening of interconnections, in the face of
a culling process, probably accounts for most neural examples of selectionism.
Quality can emerge from such carving or selective strengthening. For example, the perception of a speech sound involves
the creation of a prototype category that standardizes the meaning despite a range
of variations, and selective survival of synaptic connections within a neural feltwork is thought to contribute to categorical
perception. But -- and this is the important point for memetics -- there is nothing recursive about this type of quality enhancement.
Which of the selectionist examples should also be called "Darwinian"? I won't review the Darwinian claims except to note that, if we are to blame
anyone for the frequent confusion of selective survival with the full Darwinian
process, we would have to start with Charles Darwin himself, who named
his multipart theory (more in a minute) to emphasize one particularly novel
aspect: Natural Selection. I don't want to seem to be prescribing what's "Darwinian" and
what isn't, but I think that we must be cautious about ascribing recursive
bootstrapping of quality (what I take to be the heart of the matter,
what makes evolution so interesting) to any process that has a few elements
of the process that Darwin and followers have worked out over the last
160 years. Simulations may eventually demonstrate a semidemihemiquasi-Darwinian
bootstrap, another self-organizing process that gets better and better
-- but, until the capacities of sparse solutions are well demonstrated,
caution is in order.

Sparse Darwinian Possibilities

There are two "halfway houses" which may prove to be more
interesting than environmental carving of patterns. First, since brain
development (to continue the earlier story) is never really over (it just
slows down, and the gene repertoire may shift), and since new synapses
may form during adulthood, one is initially reminded of a biological population
with replacement and growth -- and Darwinian shaping up. But observe that
there isn't a pattern being replicated with variations; there isn't a population
of such patterns competing with other patterns, etc. -- which is what population
usually means, not merely a number of constituents comprising the pattern
being carved.
While Gerald Edelman (in his 1987 book, Neural Darwinism; see
my book review in Science7) has such a
population lacking patterned individuals, he goes beyond selectionist carving
in an interesting, nontraditional way: he has a notion of interacting maps,
that shape up one another in a manner rather like the sometimes creative back-and-forth interactions
between author and editor (my analogy, not his -- as is my perhaps shopworn
name for it, revisionism). I have a difficult time identifying either
an individual unit, or a distinctive copying mechanism for it, in Edelman's
lots-of-neurons notion of a "population," even if his re-entrant
loops are reminiscent of generations. His differential amplification via
re-entrant loops, however, is undoubtedly an important process (I particularly
like it for the consolidation of episodic memories20).
On closer inspection, neither developmental patterning nor Edelman's
reentry fits my concept of Darwin's process. Populations -- in ecology
and evolutionary biology and immunology -- usually involve lots of patterned
individuals somehow making near copies of themselves, all present at the
same time, interacting with one another and with the environment.
Yet analogies always leave something out; we don't expect them to be
perfect fits, exactly the same thing. As the poet Robert Frost once said,
we have to know how far we can ride a metaphor, judge when it's safe. That's
exactly our problem in memetics, and why Edelman's notions have proved
controversial. When, then, are we forced to ascribe, to a candidate such as developmental
patterning or reentry, the potential for the recursive bootstrapping
of quality that we associate with Darwin's process, which we regularly
see operating on the biological species and the antibody?
To approach an answer to that question, it will be useful to enumerate what has contributed
to Darwin's process, while trying to strip it of the biological particulars
-- and then ask how well it could limp along with a reduced number of components
(what I've started calling "sparse Darwinism").

The Full-fledged Darwinian
Process

The six essentials aren't a settled issue. What I was aiming for, however, were the essential ingredients of an algorithmic quality-improvement process20, stated in a way that didn't impose a lot of biological preconditions. I
wanted, for example, to avoid making use of the genotype-phenotype21 distinction, or a universal translation table like the genetic code;
I wanted to describe a process, not make an analogy. John Holland's computational technique10 known as the "genetic algorithm" comes close to what I had in mind, but Holland was trying to mimic recombination genetics in a computational procedure for discovering solutions, and I wanted to abstract more general principles
that avoided the presumption of recombination.
Since many of us think that (properly defined) the Darwinian process is a major law of the universe, right up there with chemical bonds as
a prime generator of interesting combinations that discover stratified
stabilities2, we want it to be able to run on different substrates, each
with their own distinctive properties that may, or may not, correspond
to those seen elsewhere. So our abstraction should fit the species evolution
problem, as well as the immune response, but also be independent of media
and time scale. Here, paraphrased from The Cerebral
Code, is what I ended up with:

1. There must be a pattern
involved.

2. The pattern must be copied somehow (indeed,
that which is copied may serve to define the pattern). [Together, 1 and
2 are the minimum replicable unit -- so, in a sense, we could reduce six
essentials to five. But I'm splitting rather than lumping here because
so many "sparse Darwinian" processes exhibit a pattern
without replication.]

3. Variant patterns must sometimes be produced
by chance -- though it need not be purely random, as another process
could well bias the directionality of the small sidesteps that result.
Superpositions and recombinations will also suffice.

4. The pattern and its variant must compete
with one another for occupation of a limited work space. For example,
bluegrass and crab grass compete for back yards. Limited means the
workspace forces choices, unlike a wide-open niche with enough resources
for all to survive. Observe that we're now talking about populations
of a pattern, not one at a time.

5. The competition is biased by a multifaceted
environment: for example, how often the grass is watered, cut, fertilized,
and frozen, giving one pattern more of the lawn than another. That's Darwin's
natural selection.

6. New variants always preferentially occur
around the more successful of the current patterns. In biology, there
is a skewed survival to reproductive maturity (environmental selection
is mostly juvenile mortality) or a skewed distribution of those adults
who successfully mate (sexual selection). This is what Darwin later called
an inheritance principle. Variations are not just random jumps from
some standard starting position; rather, they are usually little sidesteps
from a pretty-good solution (most variants are worse than a parent, but
a few may be even better, and become the preferred source of further variants).

Neural patterning in development is a sparse case: just a pattern and
a multifaceted environment. There is no replication of the pattern, no
variation, no population of the pattern to compete with a variant's population,
and there's nothing recursive about achieving quality because there's no
inheritance principle.

Example: History as a Darwinian
Process

History qua history -- what it includes,
what it leaves out, and how these change over time -- provides us with
a memetic example of these six essentials at work. Of the many happenings,
some are captured in patterned sentences that describe who did what to whom, why,
and with what means.

Some of these patterns are retold (copied), often with
little confusions (variation) and conflations (superpositions).
Alternative versions of stories compete for the limited space of
bookstore shelves or the limited time of campfire storytelling. There is
a multifaceted environment that affects their success, the association
of the described events to those of everyday life. In particular, the environment
contains mental schemas and scripts; as Aristotle noted and all four-year-olds
demanding bedtime stories seem to know, a proper narrative has a beginning,
middle, and end -- and so "good stories" fare much better in
the memorized environment. (Especially those conveyed by historical novels
that strengthen the narrative aspects!) Finally, because historians rewrite
earlier historians, we see Darwin's inheritance principle in action: new
variations are preferentially based on the more successfully copied of
the current generation of historical stories, and so history has a
drift to better and better fits to language instincts (such as chunking
and narratives) because current relevance is shifting and ephemeral.

After many generations, only those stories of timeless relevance are
left alongside the likely-ephemeral contemporary ones.
Quality emerges,
in some sense, as in the way that the nine-part epic tales studied by Misia
Landau (youth sets out on a quest, fails, returns, sets out again with
a helper, survives a new set of trials and tribulations, finally succeeds
and returns home, and so on12) seem to have emerged in many cultures from
the retelling of simpler narratives, generation after generation. Our modern
origin stories, the anthropological scenarios about human ancestors during
the tribulations of the ice age climate changes, are even said to follow
the epic template!
Can history, as we know it, run on a reduced set -- say, without the inheritance principle? (Imagine storytellers always reviewing a videotape
before telling the story again, so variations were always done from an
unchanging "standard version.") Certainly, a pattern that copied
and varied, with retelling biased by resonances with current memories of
the current population, would be impressive -- but the anchoring of the
center of variation to the standard version would keep stories from drifting
very far and prevent the recursive bootstrapping of quality.
Suppose that, instead of eliminating inheritance, we loosened the environmental
influence -- say, individuals' memories20 for unique episodes
faded within a year. The often-told tales would simply drift, adapting
to current concerns, losing those of the antepenultimate generation. It
would be about like the whale songs that drift from
one year to the next. What you would lose, lacking a good memorized environment
that persisted a lifetime to overlap several generations, would be shaping
up of quality (those timeless stories with universal relevance, the resonance
with episodes recurring only twice in a lifetime, and so forth).
My first "knock-out mutation" sounds, of course, like what
we try to train scholars to do ("Avoid secondary sources! Read the
original!"), while my second is merely an exaggerated version of the
ahistoricism of preliterate societies16 (the Navajo
emigrated from the Yukon to the American Southwest about 500 years ago,
but this great migration has been lost to them, recovered only through
a linguistic and genetic analysis of the Athabascan peoples). History,
however, is not merely the retention of facts: it involves detecting patterns
and attempting to understand them -- and this involves making good guesses
and refining them. That intellectual endeavor is, I suggest in How
Brains Think, another full-fledged Darwinian process.
Competition between concepts is, of course, one of the ways in which science advances; evolutionary epistemology13 treats this as a Darwinian process. The advance of science differs from ordinary history because the environment biasing the competition between concepts involves a broad range of testing against reality.

Nonessentials: Catalysts
and Stabilizers

There are another five features that, while not
essential, do notably influence the rate of evolutionary change:

7. Stability may occur, as in getting stuck
in a rut (a local minimum -- or maximum -- in the adaptational landscape). Variants happen,
but they're either nonviable or backslide easily.

8. Systematic recombination (crossing
over, sex) generates many more variants than do copying errors and the
far-rarer point mutations. Or, for that matter, nonsystematic recombination
such as bacterial conjugation or the conflation of ideas.

9. Fluctuating environments (seasons, climate
changes, diseases) change the name of the game, shaping up more complex
patterns capable of doing well in several environments. For such jack-of-all-trades
selection to occur, the climate must change much faster than efficiency
adaptations can track it (more in a minute).

10. Parcellation (as when rising sea
level converts the hilltops of one large island into an archipelago of
small islands) typically speeds evolution. It raises the surface-to-volume
ratio (or perimeter-to-area ratio) and exposes a higher percentage of the population to
the marginal conditions on the margins.

11. Local extinctions (as when an island
population becomes too small to sustain itself) speed evolution because
they create empty niches. The pioneers that rediscover the niche get
a series of generations with no competition, enough resources even for
the odder variants that would never grow up to reproduce under any competition.
For a novel pattern, that could represent the chance to "establish
itself" before the next climate change, for which it might prove better
suited than the others.

There are also catalysts acting at several removes, as in Darwin's example
of how the introduction of cats to an English village could improve the
clover in the surrounding countryside: The (i) cats would (ii) eat the
mice that (iii) attack the bumble bee nests and thus (iv) allow more flowers
to be cross pollinated. (You can see why I call these the "Rube Goldberg
Variations.")

The Augmented Darwinian Set

Although a Darwinian process will run without these catalysts, using
Darwinian creativity often requires some optimization for speed. In the
behavioral setting I analyze in my two 1996 books, quality must be achieved
within the time span of thought and action.
Accelerating factors are the problem in what the French call avoir
l'esprit de l'escalier -- finally thinking of a witty reply, but only
after leaving the party. Some accelerating factors are almost essential
in mental darwinism, simply because of the time windows created by fleeting
opportunities, and so this "augmented Darwinian set" may also prove
to be important for other memetic applications of the universal Darwinian
process.

DISCUSSION

I am proposing a standard Darwinian set (six ingredients,
in my formulation), with nonstandard cases often described via the sparse
and augmented sets. As with Edelman's reentry, some cases may be both sparse
and have a novel feature like revisionism (mixed cases). I was delighted to discover that my (neocortical circuitry) candidate process
was not only capable of implementing all six essentials, but stability
and the four catalysts as well.
At what point can we carry over the traditional implications of the best-studied case, the species-evolution Darwinian process, to a candidate
process? My present answer would be: When the six essentials are present,
and no obvious stability or relative-rate issue seems to be precluding
"progress," we are then entitled to predict that our candidate
process is capable of repeatedly bootstrapping quality. The extent of "coverage" of memetic theories varies widely.
For example, I was able to spend much of my last chapter of The Cerebral Code discussing the Darwinian implications of minor circuit malfunctions for a broad range of pathophysiology such as
seizures, hallucinations, delusions, amnesia, déjà vu, and
so forth. My point is that candidate processes in other memetic fields are also likely to
be judged by similar nonevolutionary considerations, so we must remember
that possessing the six essentials is only a "threshold" consideration,
mostly relevant to the sorts of quality that can be bootstrapped -- and
for how long that improvement can continue.

Stratified Stability and Relative
Rates

One coverage issue that seems relevant, however, is whether new levels
of organization emerge from the candidate evolutionary process. Can, for
example, a candidate process form categories? Can it progress to evolving
analogies4 or metaphors? Are these new levels ephemeral, or stable for awhile?
Jacob Bronowski spoke of "stratified
stability" and observed2, "The stable units that compose one level
or stratum are the raw material for random encounters which produce higher
configurations, some of which will chance to be stable....Evolution is
the climbing of a ladder from simple to complex by steps, each of which
is stable in itself." Does the process self-limit when reaching an
angle of repose18, so that piling on another layer
is self defeating? Does the process backslide in a catastrophic manner,
requiring something like the Weismannian barrier between genotype
and phenotype21 to provide a ratchet?
Relative rates play an important role in any process involving change,
one that can trivialize or magnify. Relative rates of expansion are the
major principle underlying most household bimetalic-layer thermostats,
and it is a familiar principle in development (the way curved surfaces
are made is to have two sheets of cells in contact, one growing faster
than the other). And we've already seen two examples here: the history
example of episodic memories that faded quickly when compared to the generation
time and lifespan, and again in #9 where climate changes had to be much
faster than adaptations could track, if jack-of-all-trades abilities were
to accumulate in the face of competition from lean, mean machines.

Repackaging the Essentials

Someone will surely try to condense my six essentials to a phrase more
memorable than "a pattern that copies with occasional
variation, where populations of the variants compete for
a limited workspace, biased by a multifaceted environment, and with
the next round of variations preferentially done from the more successful of the
current generation." Indeed, Alfred Russel
Wallace did a pretty good job back in 1875 ("...the known laws
of variation, multiplication, and heredity... have probably sufficed....")14.
It's just that I make explicit the pattern, the work space competition
between populations, and the environmental biases. As noted in #2, I'm
trying to avoid lumping where I know that splitting is going to be required
later, to deal with some important partial cases. Wallace shows us that
only three items cover a lot of essential ground, and there are surely
other profitable ways to split and lump, if context allows the inference
of other factors. A list of essentials -- at least one that aspires to
some universality -- can't omit the context, can't skip over the potential
confusions. Bronowski once observed1 that,
even if six sentences might serve to sum up one of his lectures, the rest
of the hour was really essential for disambiguating the meaning of those
summary sentences. The name of the game here isn't compression but abstraction,
an abstraction that is just general enough to cover a number of situations
that differ widely in media and time scale -- but not so abstract as to
lose important associations.
Of course, all the definition in the world can be upset by one little
existence proof, a simulation of a self-organizing quality bootstrap that
runs on a different set of principles. Until then, we are simply trying
to clarify our thinking about the creation-of-quality process we know best, the one
first stumbled upon by Charles Darwin.

Jacob Browonski, The Ascent of Man
(Little, Brown 1973), pp. 348-349. In introducing stratified
stability, Bronowski says: "Nature works by steps. The atoms form
molecules, the molecules form bases, the bases direct the formation of
amino acids, the amino acids form proteins, and proteins work in cells.
The cells make up first of all the simple animals, and then the sophisticated
ones, climbing step by step. The stable units that compose one level or
stratum are the raw material for random encounters which produce higher
configurations, some of which will chance to be stable.... Evolution is
the climbing of a ladder from simple to complex by steps, each of which
is stable in itself."

William H. Calvin, How
Brains Think: Evolving Intelligence, Then and Now (BasicBooks 1996).

William H. Calvin, The
Cerebral Code: Thinking a Thought in the Mosaics of the Mind (MIT
Press 1996). In searching for Hebb's cell assembly (a committee of neurons whose firing represents a color, word, thought, etc.), I looked for neural circuitry in the brain that was capable of copying spatiotemporal firing patterns. The top layers of the newer parts of cerebral cortex indeed have recurrent excitatory circuitry that should produce synchronized triangular arrays of neurons which extend themselves over a few centimeters, or recruit distant populations via corticocortical pathways. Collections of such arrays constitute a spatiotemporal pattern with great redundancy. The smallest "tile" in this mosaic, which has no redundancy within it, is hexagonal in shape and about 0.5 mm across; it probably has a few hundred independent elements. This is a minimal replicable unit (and a candidate for a cerebral code for, say, a word or concept); a hexagonal mosaic of it can compete with another pattern's hexagonal mosaic for territory in association cortex.

Alfred Russel Wallace, "The limits of
natural selection as applied to man," chapter 10 of Contributions
to the Theory of Natural Selection (Macmillan 1875).

John Z. Young, A Model of the Brain
(Claredon Press 1964). His "The organization of a memory system,"
Proceedings of the Royal Society (London) 163B:285-320 (1965) introduces
the mnemon concept in which weakened synapses serve to tune up a function.
A later version is his "Learning as a process of selection,"
Journal of the Royal Society of Medicine 72:801-804 (1979). The
modern chapter of mental darwinism starts in 1965 with Daniel C. Dennett's D.
Phil. thesis, published as Content and Consciousness (Routledge
and Kegan Paul 1969) but it all began more than a century ago with William James, "Great men, great thoughts, and the environment," The Atlantic Monthly 46(276):441-459 (October 1880).

Ahistoricism is discussed in the
first
chapter of my book, The River That Flows Uphill. But Loren Eiseley
said it best: "Man without writing cannot long retain his history
in his head. His intelligence permits him to grasp some kind of succession
of generations; but without writing, the tale of the past rapidly degenerates
into fumbling myth and fable. Man's greatest epic, his four long battles
with the advancing ice of the great continental glaciers, has vanished
from human memory without a trace. Our illiterate fathers disappeared and
with them, in a few scant generations, died one of the great stories of
all time."

An algorithm is a simple systematic
procedure for solving a problem, usually involving repeated steps, e.g.,
long division (try multiplying the divisor by two and subtracting; if the
remainder is too large, try 3, etc.).

The angle of repose is a geological term
for how steep-sided a pile can become before little landslides remove any
further additions.

Bootstrapping ("Pulling yourself
up by your own bootstraps") is a term that describes the ability of
simple patterns to bring forth more complicated ones. A familiar example
is the start-up procedure for a computer: booting involves a simple program
stored in a ROM chip that, in turn, reads and starts up the operating system
from a hard disk -- which, in turn, starts up the application programs.

Episodic memories are those of unique
events, such as a particular conversation; they're much more difficult
to maintain than memories of repeated events. Consolidation
of memory is the often-fallible process of making
short-term "volatile" memories into more permanent long-term
memories with an enduring structural basis. I suggest, in
chapter
6 of The Cerebral Code, that Edelmanian revisionism, between
a hippocampal map and a cortical map, would be a useful way of "learning"
(via repeated trials) what was originally only a unique episode and embedding
it in neocortex. Like a photographic development process, it is likely that, in the manner of those three-million-year old footprints that were preserved by volcanic ashfall (cement on the fly preventing the
usual erosion and backfilling), both culling and fixation are involved in biological memories.

Weismann's genotype-phenotype distinction in
biology is not a necessary condition for a Darwinian process, as recent
experiments on "RNA evolution" have shown (there isn't a body
that lives and dies, carrying the genes along, but rather patterns directly
exposed to environmental selection). Envelopes such as bodies (phenotypes)
are an example of stratified stability; they nicely illustrate why strict one-trait-at-a-time adaptationist reasoning is insufficient. Genes often live -- and die -- in a collection called an "individual," which means that success is often via particular combinations of traits.